Dekubap

Dekubap — CS2 Stats

76561198355506837[U:1:395241109]Steam profile ↗✓ No bans

1,597Tracked matches64%Win rate2020Tracked since
CSDB Rating6.5 SolidOpening Duellist
Premier CS Rating15,121Purple band · top ~27.9% of ranked players (population est.)
WingmanThe Global Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 27 Oct 2026 (9 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 15,121 -605 15 Feb – 27 Oct · 21 days played
12,80615,726peak 15,72615 Feb27 Oct
15,726Peak Premier in tracked matches
2,094Highest Faceit ELO seen on CSDB
69Days played since 2026-01-22

Faceit ELO

  • At peak — 2,094
  • Next: 2,500 ELO at 2,500 — 406 to go
  • Reached: Level 10 · Level 9 · Level 8 · Level 7

Premier CS Rating

  • 605 below peak (15,726)
  • +122 over 30 days · steady
  • Next: Pink band at 20,000 — 4,879 to go
  • Reached: Purple band · Blue band · Light Blue band

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Share this profile

CSDB.GGDekubapPREMIER15,121 · Purple bandPEAK ELO2,094csdb.gg/stats

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Performance scores

Aim74
Positioning62
Utility54

0–100 skill scores via Leetify.

Recent form

HOT51–44–5Last 10051%Win rateWWLTWWLWWW

Last 10 vs previous 10: +20pp win rate · −0.05 avg rating · −7.4pp headshot accuracy · +117ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.05), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–1–1 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 19%
  • Avg reaction 600ms

Last 10

  • 7–2–1 · 70% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 18%
  • Avg reaction 600ms

Last 20

  • 12–7–1 · 60% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 22%
  • Avg reaction 541ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Opening Duellist — Winning opening duels is what stands out in this profile (+1.3 against its own average). How often you WIN the first duel — CSDB cannot yet see how often you take it.

Aim7.4
Utility5.4
Positioning6.2
Opening Duels6.8
Clutch3.6

Strong CT-side opener

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

s1mple

Plays most like s1mple 90% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Strengths

CT openings. 65% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 65% on CT to 34% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 589ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim7.4
Positioning6.2
Utility5.4
Mechanics5.2
Opening Duels4.9
Win Impact9.8

Composite 6.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.02
first ⅓ avg 0.01 → last ⅓ avg 0.02
Reaction time568ms−87ms
first ⅓ avg 654ms → last ⅓ avg 568ms
Headshot accuracy24.4%+4.9%
first ⅓ avg 19.5% → last ⅓ avg 24.4%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.35Best match rating · 9–3 · poseidon, 2 Apr →
45%Best headshot accuracy · 13–9 · mirage, 9 Aug →
375msFastest reaction time · 10–13 · cache, 18 Aug →
13–0Biggest win · mirage, 28 Jan →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W2Current streak
6–6In matches decided by ≤2 rounds
5Overtime games

Map breakdown

debrisBest map · 80% over 5infernoWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
mirageB2914–1548%0.01
poseidonB126–650%0.06
cacheA116–555%0.01
dust2S96–367%0.01
ancientA74–357%0.01
infernoD72–529%-0.00
debrisS54–180%0.05
nukeA53–260%0.02
overpassC52–340%-0.03
anubis—41–325%-0.01
train—20–20%-0.05
eldorado—22–0100%0.06
vertigo—10–10%-0.08
office—11–0100%0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,166Matches
52%Win rate
1.01Avg K/D
80.7ADR
54%Headshot %

Clutches & streaks

38%1v1 clutch win
22%1v2 clutch win
12Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage33851%0.9915.9
Dust219056%1.0316.1
Nuke8753%1.0416.3
Inferno8746%0.9515.2
Ancient7148%0.9915.0
Anubis6549%0.9715.2
Train3847%1.0917.1
Overpass3759%1.0216.1

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

24.7%Headshot accuracy
33.4%Accuracy (enemy spotted)
36.4%Spray accuracy
73.5%Counter-strafing
8.7°Preaim
589msReaction time
34.0%T opening success
65.4%CT opening success
0.64Enemies flashed / flash
8.6%Flash assists
8.46HE damage / grenade
9.87Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 34.013% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–9-0.0516%27 Oct →
cache13–90.0627%23 Oct →
inferno14–16-0.0515%14 Oct →
train12–12-0.0622%8 Oct →
mirage13–20.1313%6 Oct →
cache13–30.0917%27 Sept →
cache4–13-0.104%11 Sept →
mirage13–7-0.0031%10 Sept →
mirage13–9-0.0011%9 Sept →
cache13–70.0426%9 Sept →
debris9–40.1924%9 Sept →
inferno10–13-0.0423%7 Sept →
cache11–130.0841%3 Sept →
dust26–13-0.0429%30 Aug →
mirage13–30.0832%28 Aug →
ancient6–00.1813%28 Aug →
debris9–40.0726%26 Aug →
mirage13–50.0726%23 Aug →
inferno6–130.0326%21 Aug →
cache10–13-0.0917%18 Aug →
mirage13–70.0425%17 Aug →
dust25–13-0.0641%15 Aug →
mirage12–12-0.0313%13 Aug →
nuke13–7-0.0132%13 Aug →
cache6–130.0119%10 Aug →
mirage13–90.0345%9 Aug →
debris9–6-0.0920%30 Jul →
debris9–40.1637%16 Jul →
debris4–9-0.0628%13 Jul →
eldorado9–20.0635%11 Jul →
eldorado9–70.0710%11 Jul →
dust213–100.0424%26 Jun →
inferno13–20.0139%15 May →
cache13–11-0.0140%10 May →
cache7–13-0.0221%8 May →
cache13–10-0.0212%7 May →
cache13–80.0334%2 May →
vertigo6–13-0.0811%8 Apr →
mirage10–13-0.0413%2 Apr →
poseidon3–9-0.1610%2 Apr →
poseidon9–30.3540%2 Apr →
ancient13–80.0821%30 Mar →
inferno13–90.0923%22 Mar →
nuke7–130.0437%20 Mar →
office13–80.0132%19 Mar →
mirage5–11-0.0821%18 Mar →
anubis12–16-0.0025%12 Mar →
overpass7–13-0.0429%12 Mar →
poseidon8–80.0714%11 Mar →
poseidon9–50.1417%11 Mar →
overpass13–1-0.017%11 Mar →
overpass8–13-0.0641%11 Mar →
inferno10–130.0123%10 Mar →
mirage11–13-0.0212%8 Mar →
mirage11–130.0212%5 Mar →
mirage13–100.0415%3 Mar →
ancient1–13-0.108%3 Mar →
poseidon4–9-0.0524%1 Mar →
poseidon9–50.0132%28 Feb →
train2–13-0.0414%25 Feb →
mirage6–13-0.0428%25 Feb →
anubis13–80.0422%25 Feb →
dust213–90.1926%24 Feb →
poseidon9–40.0532%21 Feb →
ancient13–10.0414%20 Feb →
mirage7–13-0.0131%20 Feb →
mirage5–130.0517%18 Feb →
mirage11–130.0324%18 Feb →
overpass4–13-0.0610%16 Feb →
nuke13–4-0.0026%16 Feb →
mirage13–110.0023%15 Feb →
mirage16–130.0124%14 Feb →
dust213–80.0324%13 Feb →
nuke9–13-0.0118%13 Feb →
mirage13–110.0721%13 Feb →
poseidon5–90.0023%12 Feb →
poseidon9–10.0818%12 Feb →
dust213–11-0.0418%11 Feb →
mirage9–13-0.0514%11 Feb →
inferno5–13-0.0618%11 Feb →
nuke13–30.0622%8 Feb →
anubis12–12-0.0125%6 Feb →
mirage13–80.0512%6 Feb →
dust213–5-0.0317%6 Feb →
dust219–170.0321%3 Feb →
mirage14–160.0113%2 Feb →
mirage4–13-0.0220%1 Feb →
overpass13–60.0338%1 Feb →
ancient7–130.0214%1 Feb →
ancient9–13-0.1117%31 Jan →
mirage9–13-0.0414%31 Jan →
mirage8–13-0.0117%28 Jan →
mirage13–00.0517%28 Jan →
poseidon8–8-0.0524%28 Jan →
poseidon9–20.1915%27 Jan →
mirage10–13-0.0326%26 Jan →
poseidon6–90.0417%25 Jan →
dust29–13-0.0017%25 Jan →
mirage13–100.0926%25 Jan →
anubis8–13-0.0612%22 Jan →

Match data via Leetify.

Recent teammates

Milestones

2K ELO1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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